2.3k citations · 2.5k across the 15 of their papers we have counts for
4 papers · 1 filter
Conditional probing: measuring usable information beyond a baseline
John Hewitt, Kawin Ethayarajh, Percy Liang +1
Probing experiments investigate the extent to which neural representations make properties -- like part-of-speech -- predictable. One suggests that a representation encodes a prope…
On the Opportunities and Risks of Foundation Models
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli +111
AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks.…
Refining Targeted Syntactic Evaluation of Language Models
Benjamin Newman, Kai-Siang Ang, Julia Gong +1
Targeted syntactic evaluation of subject-verb number agreement in English (TSE) evaluates language models' syntactic knowledge using hand-crafted minimal pairs of sentences that di…
Probing artificial neural networks: insights from neuroscience
Anna A. Ivanova, John Hewitt, Noga Zaslavsky
A major challenge in both neuroscience and machine learning is the development of useful tools for understanding complex information processing systems. One such tool is probes, i.…